no code implementations • 11 Mar 2024 • Junbin Liu, Ya Liu, Wing-Kin Ma, Mingjie Shao, Anthony Man-Cho So
This study develops a framework for a class of constant modulus (CM) optimization problems, which covers binary constraints, discrete phase constraints, semi-orthogonal matrix constraints, non-negative semi-orthogonal matrix constraints, and several types of binary assignment constraints.
no code implementations • 11 Mar 2024 • Junbin Liu, Ya Liu, Wing-Kin Ma, Mingjie Shao, Anthony Man-Cho So
In the first part of this study, a convex-constrained penalized formulation was studied for a class of constant modulus (CM) problems.
no code implementations • 26 Jan 2024 • Junbin Liu, Yuening Li, Wing-Kin Ma
Our multilayer model is based on the postulate that if we arrange the varied endmembers as an expanded endmember matrix, that matrix exhibits a low-rank structure.
no code implementations • 25 Oct 2023 • Wai-Yiu Keung, Hei Victor Cheng, Wing-Kin Ma
In this context, we may not be able to apply conventional MIMO precoding schemes, such as the simple zero-forcing (ZF) scheme, and we typically need to design the phase signals by solving optimization problems with constant modulus constraints or with discrete phase constraints, which pose challenges with high computational complexities.
no code implementations • 22 Oct 2023 • Wai-Yiu Keung, Wing-Kin Ma
The challenge with using low-resolution DACs is to overcome the detrimental quantization error effects.
no code implementations • 1 Sep 2023 • Yatao Liu, Mingjie Shao, Wing-Kin Ma
A symbol-level precoding (SLP) scheme and a zero-forcing (ZF) precoding scheme, with the new design requirement by the spatial $\Sigma \Delta$ approach being taken into account, are developed.
no code implementations • 8 Oct 2022 • Mingjie Shao, Wing-Kin Ma, Junbin Liu, Zihao Huang
In this study we analyze the convergence rate of EM for a class of approximate maximum-likelihood OMOD formulations, or, in a broader sense, a class of problems involving regression from quantized data.
no code implementations • 1 Jul 2021 • Chujun Huang, Mingjie Shao, Wing-Kin Ma, Anthony Man-Cho So
By establishing associations between the SISAL algorithm and a line-search-based proximal gradient method, we confirm that SISAL can indeed guarantee convergence to a stationary point.
no code implementations • 27 Jun 2021 • Wing-Kin Ma
The development of DECA shows foresight years ahead, in that regard.
no code implementations • 30 Mar 2021 • Yatao Liu, Mingjie Shao, Wing-Kin Ma, Qiang Li
We examine how insights arising from this perturbed ZF and VP interpretations can be leveraged to i) substantially simplify the optimization of certain SLP design criteria, namely, total or peak power minimization subject to SEP quality guarantees; and ii) draw connections with some existing SLP designs.
no code implementations • 18 Mar 2021 • Ruiyuan Wu, Wing-Kin Ma, Yuening Li, Anthony Man-Cho So, Nicholas D. Sidiropoulos
PRISM uses a simple probabilistic model, namely, uniform simplex data distribution and additive Gaussian noise, and it carries out inference by maximum likelihood.
no code implementations • 14 Dec 2020 • Xianming Li, Yongwei Huang, Wing-Kin Ma
The minimization problem is accordingly turned into a QMI problem, and the problem is solved by a restricted linear matrix inequality relaxation with additional valid convex constraints.
no code implementations • 26 Jun 2020 • Jiajin Li, Anthony Man-Cho So, Wing-Kin Ma
Many contemporary applications in signal processing and machine learning give rise to structured non-convex non-smooth optimization problems that can often be tackled by simple iterative methods quite effectively.
no code implementations • 19 Jan 2020 • Mingjie Shao, Qiang Li, Wing-Kin Ma
Recently, the use of intelligent reflecting surface (IRS) has gained considerable attention in wireless communications.
1 code implementation • 2 Jul 2019 • Ruiyuan Wu, Wing-Kin Ma, Xiao Fu, Qiang Li
Hyperspectral super-resolution (HSR) is a problem that aims to estimate an image of high spectral and spatial resolutions from a pair of co-registered multispectral (MS) and hyperspectral (HS) images, which have coarser spectral and spatial resolutions, respectively.
no code implementations • 15 Apr 2018 • Charilaos I. Kanatsoulis, Xiao Fu, Nicholas D. Sidiropoulos, Wing-Kin Ma
Third, the majority of the existing methods assume that there are known (or easily estimated) degradation operators applied to the SRI to form the corresponding HSI and MSI--which is hardly the case in practice.
no code implementations • 3 Mar 2018 • Xiao Fu, Kejun Huang, Nicholas D. Sidiropoulos, Wing-Kin Ma
Perhaps a bit surprisingly, the understanding to its model identifiability---the major reason behind the interpretability in many applications such as topic mining and hyperspectral imaging---had been rather limited until recent years.
no code implementations • 9 Aug 2017 • Chia-Hsiang Lin, Ruiyuan Wu, Wing-Kin Ma, Chong-Yung Chi, Yue Wang
This maximum volume inscribed ellipsoid (MVIE) idea has not been attempted in prior literature, and we show a sufficient condition under which the MVIE framework guarantees exact recovery of the factors.
no code implementations • 15 Aug 2016 • Xiao Fu, Kejun Huang, Bo Yang, Wing-Kin Ma, Nicholas D. Sidiropoulos
This paper considers \emph{volume minimization} (VolMin)-based structured matrix factorization (SMF).
no code implementations • 16 Jul 2015 • Xiao Fu, Kejun Huang, Wing-Kin Ma, Nicholas D. Sidiropoulos, Rasmus Bro
Convergence of the proposed algorithm is also easy to analyze under the framework of alternating optimization and its variants.
no code implementations • 7 Jul 2015 • Xiao Fu, Wing-Kin Ma, José Bioucas-Dias, Tsung-Han Chan
The dictionary-aided sparse regression (SR) approach has recently emerged as a promising alternative to hyperspectral unmixing (HU) in remote sensing.
no code implementations • 15 Sep 2014 • Xiao Fu, Wing-Kin Ma, Tsung-Han Chan, José M. Bioucas-Dias
We then perform exact recovery analyses, and prove that the proposed greedy algorithm is robust to noise---including its identification of the (unknown) number of endmembers---under a sufficiently low noise level.
no code implementations • 20 Jun 2014 • Nicolas Gillis, Wing-Kin Ma
We analyze robustness of pre-whitening which allows us to characterize situations in which it performs competitively with the SDP-based preconditioning.
no code implementations • 20 Jun 2014 • Chia-Hsiang Lin, Wing-Kin Ma, Wei-Chiang Li, Chong-Yung Chi, ArulMurugan Ambikapathi
In blind hyperspectral unmixing (HU), the pure-pixel assumption is well-known to be powerful in enabling simple and effective blind HU solutions.